docs: streamline docstrings and comments for clarity in metadata.py

[jianjunzhong]

Summary by CodeRabbit

• Chores
  • Refactored internal documentation and comments to improve code clarity and maintainability. No functional changes to system behavior.

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Walkthrough

Docstrings and inline comments in transfer_queue/metadata.py were reworded and tidied across FieldMeta, SampleMeta, and BatchMeta classes. No functional logic, behavioral semantics, or public API signatures were altered.

Changes

Cohort / File(s)	Summary
Docstring and comment restructuring transfer_queue/metadata.py	Reworded and tidied docstrings in FieldMeta, SampleMeta, BatchMeta, and helper functions; reduced inline commentary and aligned comments with code; preserved field names, types, defaults, and behavioral semantics

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

Poem

🐰 A rabbit's ode to cleaner docs 🐰

With careful paws, we brushed away
The tangled words that there did stay,
The meanings clear, the logic sound—
Just tidier prose that we have found!
No hearts were changed, just dresses worn,
And comments crisp as carrots corn. 🥕

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 27.78% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title Check	✅ Passed	The pull request title "docs: streamline docstrings and comments for clarity in metadata.py" directly and accurately reflects the primary changes in the changeset. The summary confirms that the PR focuses on reworded and tidied docstrings, minor restructuring of documentation, and reduced inline comments across multiple classes in the metadata.py file, with no functional changes. The title is specific, clear, uses the standard "docs:" prefix convention for documentation changes, avoids vague terms, and would allow a teammate scanning history to immediately understand that this is a documentation cleanup effort.

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[0oshowero0]

@coderabbitai review

[Copilot]

Pull Request Overview

This PR streamlines documentation in metadata.py by condensing multi-line docstrings into single-line format and removing redundant inline comments. The changes improve code readability while preserving all functional behavior.

Key changes:

• Converted verbose docstrings to concise single-line format following PEP 257 style
• Removed redundant inline comments that repeated obvious information
• Removed a TODO comment about checking docstrings

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[Copilot]

The simplified docstring omits important details about the function's behavior. The original docstring explained that dtype/shape are set to None when attributes are missing, and documented the set_all_ready parameter's effect on production_status (READY_FOR_CONSUME vs NOT_PRODUCED). Consider preserving this information: \"\"\"Extract field metas from a TensorDict. Sets dtype/shape to None if attributes are missing. The set_all_ready parameter controls whether production_status is READY_FOR_CONSUME (True) or NOT_PRODUCED (False).\"\"\"

Suggested change

	"""Extract field metas from a TensorDict."""
	"""
	Extract field metas from a TensorDict.
	Sets dtype and shape to None if the corresponding attributes are missing from the tensor values.
	The set_all_ready parameter controls whether production_status is READY_FOR_CONSUME (True)
	or NOT_PRODUCED (False).
	"""

[Copilot]

The simplified docstring removed important parameter documentation. The original explained the set_all_ready parameter's purpose (controlling production_status values). Consider: \"\"\"Add new fields from a TensorDict to all samples. If set_all_ready is True, sets production_status to READY_FOR_CONSUME; otherwise NOT_PRODUCED.\"\"\"

Suggested change

	"""Add new fields from a TensorDict to all samples in this batch."""
	"""
	Add new fields from a TensorDict to all samples in this batch.
	If set_all_ready is True, sets production_status to READY_FOR_CONSUME; otherwise, sets to NOT_PRODUCED.
	Args:
	tensor_dict (TensorDict): The TensorDict containing new fields to add.
	set_all_ready (bool): If True, sets production_status to READY_FOR_CONSUME for all new fields;
	otherwise, sets to NOT_PRODUCED. Default is True.
	Returns:
	BatchMeta: The updated BatchMeta instance.
	"""

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